ARTFEED — Contemporary Art Intelligence

Adaptive Test-Time Compute Allocation with Evolving Demonstrations

ai-technology · 2026-04-25

A new framework jointly adapts compute allocation and generation distribution at test time. It uses a warm-up phase to identify easy queries and build an initial pool of question-response pairs from the test set. An adaptive phase then focuses computation on unresolved queries, reshaping generation distributions via evolving in-context demonstrations that condition on successful responses from semantically related queries. Experiments on math, coding, and reasoning benchmarks show consistent outperformance over baselines with substantially less compute.

Key facts

  • Framework jointly adapts compute allocation and generation distribution at test time.
  • Warm-up phase identifies easy queries and assembles initial pool of question-response pairs from the test set.
  • Adaptive phase concentrates computation on unresolved queries.
  • Generation distributions reshaped through evolving in-context demonstrations.
  • Conditioning on successful responses from semantically related queries.
  • Experiments on math, coding, and reasoning benchmarks.
  • Outperforms existing baselines while consuming substantially less compute.

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